Non-maximum suppression is an important process used in object or feature detection. For example, an object detection algorithm may compute a score at an image pixel associated with the likelihood that pixel is the upper-left corner of a rectangle of a given size that contains the desired object. If the score is high enough, the detection produces a positive result. There could be many high scores for rectangles that are close to one another and that all contain or partially contain the same desired object. In that case, the detection algorithm should detect each object only once. The detection algorithm can do that by suppressing scores that are not locally maximum. In terms of computations and memory access, conventional non-maximum suppression techniques can be very costly.
It would be desirable to implement a block based non-maximum suppression.